Random number generation is a fundamental process in any computer system. In particular, the security of cryptographic systems depends on having a good source of random numbers. However, computers are highly deterministic in their operation and the output of any algorithm is predictable given the inputs. Accordingly, random numbers are not generated using purely algorithmic means. The generation of random numbers typically consists of two distinct phases, entropy collection and the random number generation. Entropy is information that is not predictable to attackers, and the entropy is used as a seed for a deterministic Pseudo-Random Number Generator (PRNG), which often uses cryptographic techniques. Conventional techniques for entropy collection may try to collect entropy when none is available, when none is needed, or when a device would otherwise remain in a power-conserving, idle state. For small battery-powered devices, energy-efficiency is paramount, and inefficient processor utilization can increase power consumption. Entropy collection when it is not available or needed consumes power and impacts the energy efficiency of a device.